Bus 190 – Midterm Exam Review PDF

Title Bus 190 – Midterm Exam Review
Author Marianne Rose Brusola
Course Business Finance
Institution Monash University
Pages 2
File Size 76 KB
File Type PDF
Total Downloads 27
Total Views 154

Summary

Study guide...


Description

Bus 190 – Midterm Exam – Chapters 6. 7, 9, and 13 Review Pl easef ol l ow di r ect i onsl i st edi nt hepr obl ems.Youwi l lbeusi ngExcelt osol ve mostoft hepr obl ems.

Chapter 6: 

  

Transportation problem and transshipment problem– section 6.1 o Understand how to draw and write the equations for the objective function and constraints. o Review how to use Excel to model problems and use Solver to develop answers. Assignment problem application in section 6.2 Shortest-route problem in section 6.3 Review the sample problems in the module and HW problems, especially problem #3, #5, part a and b, #13, part a and b, #25, part a

Chapter 7:    

Integer linear programming. Know how to interpret constraints in an all-integer linear program – section 7.3 Review how to determine slack in constraints. Review the samples in the module. Know that you are not solving any of the problems in chapter 7 with Excel or Solver.

Chapter 9: 

Critical path method – section 9.1



Uncertain activity time – section 9.2 o

Know how to do PERT and Critical path of a project model

o

Know the calculation formulas for solving the critical path with uncertain times, variance, standard deviation, Z-score, and probability of completing the project on given time.

o

Write the following formulas so you have them handy:

o



Expected time 9.4 on page 392



Variance 9.5 on page 392



Standard Deviation page 396



How to use Appendix B to find probability of Z-score

Practice problems #6, and #9

o

Review the HW assignment problems

Chapter 13:     

Payoff table – Know to interpret the payoffs of the decision alternatives based on the state of nature. Decision trees – know how to assign payoff amount for each branch. Know how to assign conditional probabilities to the branches of chance nodes. Decision trees and how to calculate expected value EV of the branches of a node using conditional probabilities. Decision analysis with sample information Review HW problems and practice problems o Review formula 13.4 o Review tables 13.3 and 13.5 o Review tables 13.8, 13.9, and 13.10...


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